A mixed integer linear programming model to regulate the electricity sector
Michael Polemis ()
Letters in Spatial and Resource Sciences, 2018, vol. 11, issue 2, No 7, 183-208
Abstract This paper presents a mixed-integer linear programming model for the optimal long-term electricity planning of the Greek wholesale generation system. In order to capture more accurately the technical characteristics of the problem, we have divided the Greek territory into a number of individual interacted networks (geographical zones). In the next stage we solve the system of equations and provide simulation results for the daily/hourly energy prices based on the different scenarios adopted. The empirical findings reveal an inverted-M shaped curve for electricity demand in Greece, while the system marginal price curve also follows a non-linear pattern. Lastly, given the simulations results, we provide the necessary policy implications for government officials, regulators and the rest of the marketers.
Keywords: Electricity market; Linear programming; Constraints; Day-ahead scheduling; Greece (search for similar items in EconPapers)
JEL-codes: C60 Q40 L94 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1007/s12076-018-0211-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Working Paper: A Mixed Integer Linear Programming Model to Regulate the Electricity Sector (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:spr:lsprsc:v:11:y:2018:i:2:d:10.1007_s12076-018-0211-8
Ordering information: This journal article can be ordered from
Access Statistics for this article
Letters in Spatial and Resource Sciences is currently edited by Henk Folmer and Amitrajeet A. Batabyal
More articles in Letters in Spatial and Resource Sciences from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().